Research and entrepreneurship go hand in hand
Both Thirona and Quirem are entrepreneurial organisations operating in the field of medical technology. Bram van Ginneken (Professor of Medical Image Analysis) and Frank Nijsen (medical biologist) are involved with the project as Radboudumc representatives. “This is a good form of collaboration for us,” says Van Ginneken. “We do our research and if the results are promising, it is reassuring to know that there is a company that will do something with them.” “Unfortunately, that is not always the case.” agrees Nijsen. “Another benefit is that we are all based in the same region. A region in which a lot is happening and where there is a close connection and interaction between research and entrepreneurship.”

Smart algorithms goals

For Van Ginneken, the project funded by ERDF should mainly lead to the development of useful algorithms for oncology. “An increasing number of treatment options mean that patients with cancer live longer. That also means that an increasing number of scans are made to monitor the course of the disease and its treatment. Does a tumour grow bigger or smaller? Are there more metastases that are suitable for treatment? In principle, these questions could in the future be answered by smart algorithms that automatically read and assess scans. We will be developing software that analyses the medical images of colon cancer, prostate cancer, breast cancer and bone cancer. Based on this, the treatment team will be able to plan more accurately. In this research and
development project we aim to translate knowledge into marketable products that benefit both patient and doctor. And that’s how you make impact.”

Improving accuracy for optimal treatment
The same is true for Quirem and Nijsen. They want to further refine and improve the treatment. For instance, by being able to follow the path of the microspheres in the patients, not only beforehand but also during the treatment. Nijsen: “Our microspheres can be made visible during the treatment.
If you know where they get stuck, you can also calculate the radiation that they emit. That dose can then during the treatment be compared to the dose which is needed to properly treat the tumour. It would be great if, as a result of the project, we would be able to calculate the location and size of
the tumour automatically, followed by a recommendation about the optimal dose of radiation. Those are the prospects of Radiology of the Future.”

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